Noise suppression device, noise suppression method, and reception device and reception method using same

ABSTRACT

A noise suppression device includes: a DFT executor that expands a baseband signal into a discrete Fourier series X0(n), the baseband signal being generated by mixing an AM broadcast wave signal including a carrier wave of the angular frequency ωC with a complex sine wave of the same frequency; and an amplitude spectrum calculator that calculates an amplitude spectrum |X0(n)| from X0(n). The noise suppression device also includes: an asymmetric component detector that detects an asymmetric component in |X0(n)|; a suppressor that calculates a discrete Fourier series X1(n) by multiplying the value corresponding to the asymmetric frequency bin by a first factor and multiplying the other values by a second factor in X0(n); and an IDFT executor that performs inverse discrete Fourier transform on X1(n) to obtain a discrete-time signal.

TECHNICAL FIELD

The present invention relates to a noise suppression device, a noisesuppression method, and a reception device and a reception method usingthe same in an environment where noise is superimposed on a signal bandin double-sideband-based broadcasting and communication.

BACKGROUND ART

AM radios are widespread and provided in many mobile units such asautomobiles.

Because AM radio broadcast waves are amplitude-modulated waves, noise ina signal band of a receiving station directly affects sound.

In particular, if noise generated by electric devices mounted on anautomobile such as an actuator, a motor, and a DC converter isintroduced into a signal band of a receiving station, beats occur due tothe difference between the noise frequency and the frequency of thereceiving station, resulting in unusual sound.

As a technique for reducing such noise, PTL 1 discloses a method forremoving a noise superimposed on only one of the sidebands in the RFband in a double-sideband signal. The signal is quadrature-demodulatedinto a baseband signal having a positive frequency band and a negativefrequency band. A noise component contained in the in-phase componentoutput by a demodulator is removed on the basis of the quadraturecomponent.

PTL 2 discloses a reception device by which a noise in proximity to asignal and superimposed on the signal is removed from the signal. Thereception device includes a first mixer that selectively outputs thesignal using an in-band frequency of the signal, and a second mixer thatselectively outputs only the noise in proximity to the signal using anout-of-band frequency of the signal. A noise detector receives the noisethrough a second receiver. The noise received by the noise detector issubtracted from the signal received by a main signal receiver, so thatthe noise superimposed on the received signal is removed.

CITATION LIST Patent Literature

PTL 1: International Publication No. WO2016/075878

PTL 2: Japanese Unexamined Patent Application Publication No.2004-254184

SUMMARY OF THE INVENTION Technical Problems

In the conventional technique disclosed in PTL 1, if a noise exists nearthe carrier wave in a double-sideband signal, quadrature demodulationfor extracting a noise superimposed on only one sideband in the RF bandis still required.

However, it is difficult in this case to synchronize the frequency of amixed wave to be mixed by a mixer and the frequency of the carrier wavetransmitted from a broadcast station. In addition, if multiple noisesare superimposed on the sidebands, the phase of each noise needs to berotated in a different direction, which makes the noise extractionprocessing difficult.

In the conventional technique disclosed in PTL 2, the second mixer isused that selectively outputs only a noise in proximity to a receivedsignal using an out-of-band frequency of the signal. The use of thesecond mixer requires that a frequency band allowing only a noise to beselectively output should exist in proximity to the received signal.

However, if an adjacent broadcast wave exists in proximity to thereceived signal, it is impossible to have such a frequency band thatallows only a noise to be selectively output.

The present invention has been made in view of the above circumstances,and an object thereof is to provide a noise suppression device and anoise suppression method capable of stably suppressing noise in areceived signal under various conditions.

Solutions to Problems

For accomplishing the above object, the present invention involvessuppressing an asymmetric component as a noise component by focusing onthe fact that the sideband signals in a received signal aresymmetrically disposed on the frequency axis with respect to the carrierwave signal. The present invention also involves suppressing a noisecomponent by focusing on the fact that the ratio of the amplitude of thesideband signals to the amplitude of the carrier wave signal is nothigher than a certain ratio.

More specifically, a noise suppression device according to the presentinvention includes: a discrete Fourier transform executor that expands abaseband signal into a discrete Fourier series, the baseband signalbeing generated by quadrature-demodulating a received signal having anupper sideband signal and a lower sideband signal located symmetricallyon a frequency axis with respect to a first angular frequency; anamplitude spectrum calculator that calculates an amplitude spectrum offrequency bins of the baseband signal expanded into the discrete Fourierseries; an asymmetric component detector that detects, as an asymmetricfrequency bin, a frequency bin corresponding to an asymmetric componentin the amplitude spectrum by evaluating symmetry of the amplitudespectrum with respect to a center frequency bin corresponding to thefirst angular frequency; a suppressor that, in the discrete Fourierseries expanded from the baseband signal, multiplies a valuecorresponding to the asymmetric frequency bin by a first factor, andmultiplies a value corresponding to a frequency bin other than theasymmetric frequency bin by a second factor larger than the firstfactor; and an inverse discrete Fourier transform executor that performsinverse discrete Fourier transform on the discrete Fourier seriesprocessed by the suppressor and obtains a discrete-time signal.

According to this configuration, computational processing is performedby utilizing the fact that the pair of sideband signals in an originalsignal is symmetrically disposed on the frequency axis. This enablesstable suppression of noise with low computational complexity andwithout significant circuit-scale expansion.

It is preferable that the noise suppression device further includes: anoise component detector that compares an amplitude of a centerfrequency bin corresponding to an angular frequency of a carrier wavesignal included in the received signal and an amplitude of a frequencybin other than the center frequency bin, and detects a noise frequencybin having an amplitude whose ratio to the amplitude of the centerfrequency bin is higher than a predetermined value; a second suppressorthat, in the discrete Fourier series expanded from the baseband signal,multiplies a value corresponding to the noise frequency bin by a thirdfactor, and multiplies a value corresponding to a frequency bin havingan amplitude whose ratio to the amplitude of the center frequency bin isnot higher than the predetermined value by a fourth factor larger thanthe third factor; and an adjuster that interpolates the discrete Fourierseries processed by the second suppressor into the discrete Fourierseries processed by the suppressor and calculates a new discrete Fourierseries, wherein the discrete-time signal is obtained by the inversediscrete Fourier transform executor performing inverse discrete Fouriertransform on the new discrete Fourier series.

According to this configuration, two noise suppression processes areperformed and the resulting interpolation data is used. This enablesstable suppression of noise with low computational complexity andwithout significant circuit-scale expansion. In particular, thisconfiguration enables suppressing noises of the same amplitudesuperimposed respectively on two frequency bins located symmetricallywith respect to the component corresponding to the carrier wave.

Another noise suppression device according to the present inventionincludes: a discrete Fourier transform executor that expands a basebandsignal into a discrete Fourier series, the baseband signal beinggenerated by quadrature-demodulating a received signal having a carrierwave signal and a pair of sideband signals; an amplitude spectrumcalculator that calculates an amplitude spectrum of frequency bins ofthe baseband signal expanded into the discrete Fourier series; a noisecomponent detector that compares an amplitude of a center frequency bincorresponding to an angular frequency of the carrier wave signal and anamplitude of a frequency bin other than the center frequency bin, anddetects a noise frequency bin having an amplitude whose ratio to theamplitude of the center frequency bin is higher than a predeterminedvalue; a suppressor that, in the discrete Fourier series expanded fromthe baseband signal, multiplies a value corresponding to the noisefrequency bin by a third factor, and multiplies a value corresponding toa frequency bin having an amplitude whose ratio to the amplitude of thecenter frequency bin is not higher than the predetermined value by afourth factor larger than the third factor; and an inverse discreteFourier transform executor that performs inverse discrete Fouriertransform on the discrete Fourier series processed by the suppressor andobtains a discrete-time signal.

According to this configuration, a noise component is detected on thebasis of the ratio between the amplitude of the component correspondingto the carrier wave and the amplitudes corresponding to the otherfrequency bins. This enables stable suppression of noise with lowcomputational complexity and without significant circuit-scaleexpansion. In particular, this configuration enables suppressing noisesof the same amplitude superimposed respectively on two frequency binslocated symmetrically with respect to the component corresponding to thecarrier wave.

It is preferable that the asymmetric frequency bin comprises a pluralityof asymmetric frequency bins, and that the first factor is capable oftaking an individual value for each asymmetric frequency bin.

According to this configuration, for example if each of multipleasymmetric components has a different amplitude, a different suppressionfactor according to the amplitude can be set for each asymmetricfrequency bin. This enables more reliable suppression of the asymmetriccomponents.

Having an individual suppression factor for each frequency bin can alsoaddress the following case. For example, in the case that an asymmetricfrequency bin containing a noise component changes over reception time,the factor can be varied to prevent the effect of the time variation ofthe received signal from appearing in the demodulated sound signal.

It is possible that the frequency bin other than the asymmetricfrequency bin comprises a plurality of frequency bins, and that thesecond factor is capable of taking an individual value for eachfrequency bin other than the asymmetric frequency bin.

As in the above case, having an individual suppression factor for eachfrequency bin can prevent the effect of the time variation of thereceived signal from appearing in the demodulated sound signal.

It is preferable that the noise frequency bin comprises a plurality ofnoise frequency bins, and that the third factor is capable of taking anindividual value for each noise frequency bin.

According to this configuration, for example if each of multiple noisecomponents has a different amplitude, a different suppression factoraccording to the amplitude can be set for each noise frequency bin. Thisenables more reliable suppression of the noise components.

Having an individual suppression factor for each frequency bin can alsoaddress the following case. For example, in the case that a noisefrequency bin containing a noise component changes over reception time,the factor can be varied to prevent the effect of the time variation ofthe received signal from appearing in the demodulated sound signal.

It is possible that the frequency bin other than the noise frequency bincomprises a plurality of frequency bins, and that the fourth factor iscapable of taking an individual value for each frequency bin other thanthe noise frequency bin.

As in the above case, having an individual suppression factor for eachfrequency bin can prevent the effect of the time variation of thereceived signal from appearing in the demodulated sound signal.

It is preferable that the center frequency bin is a frequency bin havingthe greatest amplitude near a DC component in the amplitude spectrum.

According to this configuration, even if an offset exists between theangular frequency of a complex frequency mixed for generating thebaseband signal and the angular frequency of the carrier wave signal, itis possible to set the axis of symmetry in the amplitude spectrum, or toset the frequency component corresponding to the carrier wave.

It is preferable that the asymmetric component detector detects theasymmetric frequency bin by evaluating the symmetry of the amplitudespectrum based on comparison between an amplitude of one frequency binand the greatest amplitude among amplitudes of sequential frequency binsincluding a frequency bin located symmetrically to the one frequency binwith respect to the center frequency bin.

According to this configuration, the effect of deviation of thesymmetric positions of the frequency bins due to the finitefrequency-division intervals can be reduced. This enables stablesuppression of noise.

A reception device according to the present invention includes: anantenna that receives an AM broadcast wave signal output from abroadcast station; an amplifier that amplifies the AM broadcast wavesignal received from the antenna; an analog-to-digital converter thatconverts the amplified AM broadcast wave signal into a digital signal; aquadrature demodulator that quadrature-demodulates the digital signal togenerate a baseband signal; a noise suppression device according to anyone of claims 1 to 9 that suppresses a noise included in the basebandsignal to generate a discrete-time signal; and a demodulator thatdemodulates the discrete-time signal into a sound signal.

According to this configuration, having the above noise suppressiondevice enables stable noise suppression, and reception of a qualitysound signal.

A noise suppression method according to the present invention is forsuppressing a noise included in a received signal having an uppersideband signal and a lower sideband signal located symmetrically on afrequency axis with respect to a first angular frequency. The noisesuppression method includes: generating a baseband signal by mixing thereceived signal with a complex sine wave having a predetermined angularfrequency; expanding the baseband signal into a discrete Fourier series;calculating an amplitude spectrum of frequency bins of the basebandsignal expanded into the discrete Fourier series; detecting, as anasymmetric frequency bin, a frequency bin corresponding to an asymmetriccomponent in the amplitude spectrum by evaluating symmetry of theamplitude spectrum with respect to a center frequency bin correspondingto the first angular frequency; in the discrete Fourier series expandedfrom the baseband signal, multiplying a value corresponding to theasymmetric frequency bin by a first factor, and multiplying a valuecorresponding to a frequency bin other than the asymmetric frequency binby a second factor larger than the first factor; and performing inversediscrete Fourier transform on the discrete Fourier series in which theasymmetric component is suppressed and obtaining a discrete-time signal.

According to this method, computational processing is performed byutilizing the fact that the pair of sideband signals in an originalsignal is symmetrically disposed on the frequency axis. This enablesstable suppression of noise with low computational complexity.Therefore, a quality sound signal can be received.

It is preferable that the noise suppression method further includes:comparing an amplitude of a center frequency bin corresponding to anangular frequency of a carrier wave signal included in the receivedsignal and an amplitude of a frequency bin other than the centerfrequency bin, and detecting a noise frequency bin having an amplitudewhose ratio to the amplitude of the center frequency bin is higher thana predetermined value; in the discrete Fourier series expanded from thebaseband signal, multiplying a value corresponding to the noisefrequency bin by a third factor, and multiplying a value correspondingto a frequency bin having an amplitude whose ratio to the amplitude ofthe center frequency bin is not higher than the predetermined value by afourth factor larger than the third factor; and interpolating thediscrete Fourier series in which a component corresponding to the noisefrequency bin is suppressed into the discrete Fourier series in whichthe asymmetric component is suppressed, and calculating a new discreteFourier series, wherein the discrete-time signal is obtained byperforming inverse discrete Fourier transform on the new discreteFourier series.

According to this method, two noise suppression processes are performedand the resulting interpolation data is used. This enables stablesuppression of noise with low computational complexity and withoutsignificant circuit-scale expansion.

In particular, this method enables suppressing noises of the sameamplitude superimposed respectively on two frequency bins locatedsymmetrically with respect to the component corresponding to the carrierwave.

A noise suppression method according to the present invention is forsuppressing a noise included in a received signal having a carrier wavesignal and a pair of sideband signals. The noise suppression methodincludes: generating a baseband signal by mixing the received signalwith a complex sine wave having a predetermined angular frequency;expanding the baseband signal into a discrete Fourier series;calculating an amplitude spectrum of frequency bins of the basebandsignal expanded into the discrete Fourier series; comparing an amplitudeof a center frequency bin corresponding to an angular frequency of thecarrier wave signal and an amplitude of a frequency bin other than thecenter frequency bin, and detecting a noise frequency bin having anamplitude whose ratio to the amplitude of the center frequency bin ishigher than a predetermined value; in the discrete Fourier seriesexpanded from the baseband signal, multiplying a value corresponding tothe noise frequency bin by a third factor, and multiplying a valuecorresponding to a frequency bin having an amplitude whose ratio to theamplitude of the center frequency bin is not higher than thepredetermined value by a fourth factor larger than the third factor; andperforming inverse discrete Fourier transform on the discrete Fourierseries in which a component corresponding to the noise frequency bin issuppressed and obtaining a discrete-time signal.

According to this method, a noise component is detected on the basis ofthe ratio between the amplitude of the component corresponding to thecarrier wave and the amplitudes corresponding to the other frequencybins. This enables stable suppression of noise with low computationalcomplexity and without significant circuit-scale expansion. Inparticular, this method enables suppressing noises of the same amplitudesuperimposed respectively on two frequency bins located symmetricallywith respect to the component corresponding to the carrier wave.

A reception method according to the present invention includes:receiving an AM broadcast wave signal output from a broadcast station;amplifying the AM broadcast wave signal; converting the amplified AMbroadcast wave signal into a digital signal; generating a basebandsignal by mixing the digital signal with a complex sine wave having apredetermined angular frequency; suppressing a noise included in thebaseband signal to generate a discrete-time signal with any one of theabove-described noise suppression methods; and demodulating thediscrete-time signal into a sound signal.

According to this method, performing the above noise suppression stepenables stable noise suppression, and reception of a quality soundsignal.

ADVANTAGEOUS EFFECT OF INVENTION

As described above, according to the present invention, noise in asignal that includes a pair of sideband signals, such as an AM broadcastwave signal, can be stably suppressed with low computational complexity.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block configuration diagram of a reception device accordingto embodiment 1 of the present invention.

FIG. 2 is another block configuration diagram of a reception deviceaccording to embodiment 1.

FIG. 3 is a flowchart of a sound demodulation process according toembodiment 1.

FIG. 4A shows an amplitude spectrum of a baseband signal.

FIG. 4B shows an amplitude spectrum resulting from inverting theamplitude vector shown in FIG. 4A symmetrically with respect to a DCcomponent.

FIG. 4C is a diagram showing an asymmetric component in the amplitudevector.

FIG. 5 is a diagram showing an example of setting a suppression factorfor a frequency bin.

FIG. 6 shows an amplitude spectrum of a baseband signal with a noisecomponent suppressed.

FIG. 7 is a diagram showing changes of the amplitude of the noisecomponent and the suppression factor over sampling times.

FIG. 8A shows an amplitude spectrum of a baseband signal generated onthe basis of a complex sine wave having an offset angular frequency.

FIG. 8B shows an amplitude spectrum resulting from inverting theamplitude vector shown in FIG. 8A symmetrically with respect to acomponent corresponding to a carrier wave.

FIG. 8C is a diagram showing an asymmetric component in the amplitudevector.

FIG. 9 shows another example of deriving asymmetry in the amplitudespectrum of the baseband signal.

FIG. 10 is a block configuration diagram of a reception device accordingto embodiment 2 of the present invention.

FIG. 11 is a flowchart of a sound demodulation process according toembodiment 2.

FIG. 12 shows an amplitude spectrum of a baseband signal.

DESCRIPTION OF EXEMPLARY EMBODIMENTS

Hereinafter, certain exemplary embodiments are described in greaterdetail with reference to the accompanying Drawings. The embodimentsdescribed below are examples of the present invention. It should benoted that the present invention and applications and/or usages thereofare not restricted to the embodiments.

EMBODIMENT 1 Configuration of Reception Device

FIG. 1 shows a reception device according to embodiment 1. Receptiondevice 10 includes: antenna 11 that receives an AM broadcast wave signaloutput from a broadcast station; amplifier 12 that amplifies the AMbroadcast wave signal received from antenna 11; analog-to-digitalconverter (ADC) 13 that converts the amplified AM broadcast wave signalinto a digital signal; numerically controlled oscillator (NCO) 14 thatgenerates a complex sine wave; and mixer 15 that generates a basebandsignal by mixing the AM broadcast wave signal converted into the digitalsignal and the complex sine wave generated by the NCO.

NCO 14 and mixer 15 constitute quadrature demodulator 16. The basebandsignal generated by mixer 15 is a signal separated into the I (in-phase)signal and the Q (quadrature-phase) signal.

Reception device 10 also includes: discrete Fourier transform (DFT)executor 17 that expands the baseband signal into a discrete Fourierseries; amplitude spectrum calculator 18 that calculates the amplitudespectrum of the baseband signal expanded into the discrete Fourierseries; asymmetric component detector 19 that detects an asymmetricfrequency component by evaluating the symmetry between the componentscorresponding to the upper sideband and the components corresponding tothe lower sideband in the amplitude spectrum; suppressor 20 thatsuppresses the value corresponding to the asymmetric frequency componentin the discrete Fourier series; inverse discrete Fourier transform(IDFT) executor 21 that converts the discrete Fourier series subjectedto the suppression processing into a discrete-time signal; anddemodulator 22 that demodulates the discrete-time signal into a soundsignal.

As shown in FIG. 1, reception device 10 may include speaker 23 foroutputting the sound signal.

DFT executor 17, amplitude spectrum calculator 18, asymmetric componentdetector 19, suppressor 20, IDFT executor 21, and demodulator 22 arerealized as functional blocks, for example by a general-purposeprocessor in a baseband LSI performing computation. These functions mayall be implemented on a single LSI or may be implemented on multipleLSIs. These functions may reside as dedicated functional blocks on theLSI(s).

For setting suppression factors (to be described below), suppressionfactor setter 20 a may be separately provided as shown in FIG. 2.

As will be described below, noise suppression processing is realized bysubjecting the baseband signal generated by quadrature demodulator 16 tosignal processing sequentially through the functional blocks from DFTexecutor 17 to IDFT executor 21, which constitute noise suppressiondevice 30.

Sound Demodulation Process for AM Broadcast Wave Signal

A sound demodulation process will be described below. This process isperformed when the reception device shown in FIG. 1 receives an AMbroadcast wave signal having a noise superimposed thereon. In thisembodiment, the noise is assumed to be a single signal having a singlefrequency in a band occupied by sound content.

Firstly, a noiseless AM broadcast wave signal will be described.

An AM broadcast wave signal V₀(t) output from a broadcast station andreceived by the antenna is expressed by Equation 1.

[Expression 1]

V ₀(t)=A·{1+m·S(t)}·cos(ω_(C) t)  (Equation 1)

Here, m is the modulation factor, S(t) is sound content, ω_(C) is theangular frequency of the carrier wave, and A is the amplitude of thecarrier wave.

With the sound content replaced with a single-tone signal cos(ω_(S)t)having the angular frequency ω_(S), V₀(t) is expressed by Equation 2.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 2} \right\rbrack & \; \\\begin{matrix}{{V_{0}(t)} = {A \cdot \left\{ {1 + {m \cdot {\cos \left( {\omega_{S}t} \right)}}} \right\} \cdot {\cos \left( {\omega_{C}t} \right)}}} \\{= {{A \cdot {\cos \left( {\omega_{C}t} \right)}} + {\frac{A \cdot m}{2} \cdot {\cos \left( {\left\{ {\omega_{C} + \omega_{S}} \right\} t} \right)}} +}} \\{{\frac{A \cdot m}{2} \cdot {\cos \left( {\left\{ {\omega_{C} - \omega_{S}} \right\} t} \right)}}}\end{matrix} & \left( {{Equation}\mspace{14mu} 2} \right)\end{matrix}$

As indicated by Equation 2, the AM broadcast wave signal as asingle-tone signal is a summation signal that includes the carrier wavesignal having the angular frequency ω_(C) and the upper sideband (USB)signal and the lower sideband (LSB) signal having signal frequenciesshifted by ω_(S) upward and downward from the carrier wave signal,respectively. The upper sideband and the lower sideband have symmetricamplitude spectra with respect to the carrier wave.

It is to be noted that, in any AM broadcast wave signal irrespective ofwhether it is a single-tone signal, the upper sideband and the lowersideband have symmetric amplitude spectra with respect to the carrierwave.

Next, the case in which a signal received by the antenna has a noisesuperimposed thereon will be considered. In this case, the signal V(t)input to the antenna is expressed by Equation 3.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 3} \right\rbrack & \; \\\begin{matrix}{{V(t)} = {{V_{0}(t)} + {B \cdot {\cos \left( {\left\{ {\omega_{C} + \omega_{B}} \right\} t} \right)}}}} \\{= {{A \cdot {\cos \left( {\omega_{C}t} \right)}} + {\frac{A \cdot m}{2} \cdot {\cos \left( {\left\{ {\omega_{C} + \omega_{S}} \right\} t} \right)}} +}} \\{{{\frac{A \cdot m}{2} \cdot {\cos \left( {\left\{ {\omega_{C} - \omega_{S}} \right\} t} \right)}} + {B \cdot {\cos \left( {\left\{ {\omega_{C} + \omega_{B}} \right\} t} \right)}}}}\end{matrix} & \left( {{Equation}\mspace{14mu} 3} \right)\end{matrix}$

B is the amplitude of the noise, and ω_(B) is the angular frequency ofthe noise with respect to the carrier wave. The equation indicates thatthe noise is superimposed at an angular frequency that is ω_(B) awayfrom the angular frequency ω_(C) of the carrier wave signal.

FIG. 3 shows a flowchart of a sound demodulation process for thissignal.

For demodulating sound in a digital circuit, the AM broadcast wavesignal V(t) is converted into a digital signal (step S1). While the AMbroadcast wave signal V(t) needs to be input to ADC 13 for conversioninto a digital signal, the signal V(t) has a low voltage level relativeto the input dynamic range of ADC 13 because the signal V(t) has beenpropagated through space. This may cause some information in the signalV(t) to be missing in an output signal from ADC 13.

Therefore, V(t) is amplified by amplifier 12 before being input to ADC13.

The AM broadcast wave signal V′(t) amplified by amplifier 12 isexpressed by Equation 4.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 4} \right\rbrack & \; \\\begin{matrix}{{V^{\prime}(t)} = {{A^{\prime} \cdot \left\{ {1 + {m \cdot {\cos \left( {\omega_{S}t} \right)}}} \right\} \cdot {\cos \left( {\omega_{C}t} \right)}} + {B^{\prime} \cdot}}} \\{{\cos \left( {\left\{ {\omega_{C} + \omega_{B}} \right\} t} \right)}} \\{= {{{A^{\prime} \cdot \cos}\left( {\omega_{C}t} \right)} + {{\frac{A^{\prime} \cdot m}{2} \cdot \cos}\left( {\left\{ {\omega_{C} + \omega_{S}} \right\} t} \right)} +}} \\{{{\frac{A^{\prime} \cdot m}{2} \cdot {\cos \left( {\left\{ {\omega_{C} - \omega_{S}} \right\} t} \right)}} + {B^{\prime} \cdot {\cos \left( {\left\{ {\omega_{C} + \omega_{B}} \right\} t} \right)}}}}\end{matrix} & \left( {{Equation}\mspace{14mu} 4} \right)\end{matrix}$

A′ is the amplitude of the carrier wave amplified by amplifier 12, andB′ is the amplitude of the noise amplified by amplifier 12. V′(t) isinput to ADC 13, which outputs the digitized signal V′(t).

The digital signal V′(t) is then quadrature-demodulated with a complexsine wave exp(−j ω_(C)t) of the angular frequency ω′_(C) generated byNCO 14, and converted into a baseband signal that includes the I signaland the Q signal (step S2).

The angular frequency ω′_(C) of the complex sine wave generated by NCO14 does not need to strictly match the angular frequency ω_(C) of thecarrier wave. The phase of the complex sine wave also does not need tostrictly match the phase of the carrier wave.

The baseband signal in the case that the angular frequency ω_(C) of thecomplex sine wave generated by NCO 14 is such that ω′_(C)=ω_(C) isexpressed by Equation 5.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 5} \right\rbrack & \; \\{{{V^{\prime}(t)} \cdot e^{{- j} \cdot \omega_{C}^{\prime} \cdot t}} = {{{V^{\prime}(t)} \cdot e^{{- j} \cdot \omega_{C} \cdot t}} = {{V^{\prime}(t)} \cdot \left( {{\cos \left( {\omega_{C} \cdot t} \right)} - {j \cdot {\sin \left( {\omega_{C} \cdot t} \right)}}} \right.}}} & \left( {{Equation}\mspace{14mu} 5} \right)\end{matrix}$

The baseband signal expressed by Equation 5 is expanded, and filtered bya low-pass filter (LPF, not shown) to remove the componentscorresponding to the angular frequency ω_(C) of the carrier wave,resulting in a signal V″(t) (step S3).

Letting I(t) and Q(t) be the real part and the imaginary part of V″(t),respectively, I(t) and Q(t) are expressed by Equations 6 and 7,respectively.

$\begin{matrix}\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 6} \right\rbrack & \; \\\begin{matrix}{{I(t)} = {{V^{''}(t)} \cdot {\cos \left( {\omega_{C} \cdot t} \right)}}} \\{= {{\frac{1}{2}A^{\prime}} + {\frac{1}{2}{A^{\prime} \cdot m \cdot {\cos \left( {\omega_{S} \cdot t} \right)}}} + {\frac{1}{2}{B^{\prime} \cdot {\cos \left( {\omega_{B} \cdot t} \right)}}}}}\end{matrix} & \left( {{Equation}\mspace{14mu} 6} \right)\end{matrix} & \; \\\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 7} \right\rbrack & \; \\\begin{matrix}{{Q(t)} = {{- {V^{''}(t)}} \cdot {\sin \left( {\omega_{C} \cdot t} \right)}}} \\{= {{- \frac{1}{2}}{B^{\prime}\; \cdot {\sin \left( {\omega_{B} \cdot t} \right)}}}}\end{matrix} & \left( {{Equation}\mspace{14mu} 7} \right)\end{matrix} & \;\end{matrix}$

The result of amplitude-demodulating the baseband signal I(t), Q(t) isexpressed by Equation 8.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 8} \right\rbrack & \; \\\begin{matrix}{{Y(t)} = \sqrt{{I(t)}^{2} + {Q(t)}^{2}}} \\{= \left\{ \left( {{\frac{1}{2}A^{\prime}} + {\frac{1}{2}{A^{\prime} \cdot m \cdot \cos}\left( {\omega_{s} \cdot t} \right)} +} \right. \right.} \\{{\left. \quad{\frac{1}{2}{B^{\prime} \cdot {\cos \left( {\omega_{B} \cdot t} \right)}}} \right)^{2} +}} \\{\left. \quad\left( {{- \frac{1}{2}}{B^{\prime}\; \cdot {\sin \left( {\omega_{B} \cdot t} \right)}}} \right)^{2} \right\}^{\frac{1}{2}}} \\{= \left\{ {\left( {\frac{A^{\prime}}{2} + {\frac{A^{\prime} \cdot m}{2} \cdot {\cos \left( {\omega_{S} \cdot t} \right)}}} \right)^{2} + \frac{B^{\prime 2}}{4} +} \right.} \\{{\frac{A^{\prime} \cdot B^{\prime}}{2}\left\lbrack {{\cos \left( {\omega_{B} \cdot t} \right)} + {\frac{m}{2} \cdot}} \right.}} \\{{{\cos \left( {\left( {\omega_{S} + \omega_{B}} \right)t} \right)} + {\frac{m}{2} \cdot}}} \\\left. \left. {\cos \left( {\left( {\omega_{S} - \omega_{B}} \right)t} \right)} \right\rbrack \right\}^{\frac{1}{2}}\end{matrix} & \left( {{Equation}\mspace{14mu} 8} \right)\end{matrix}$

As can be seen from Equation 8, if a noise is introduced into the AMbroadcast wave signal from the broadcast station before the signal isreceived by antenna 11, the result of amplitude demodulation containsnot only a component of the noise frequency ω_(B); it also contains acomponent of an angular frequency of the sum of the noise frequencyω_(B) and the angular frequency ω_(S) of the sound content, and acomponent of an angular frequency of the difference between the noisefrequency ω_(B) and the angular frequency ω_(S) of the sound content.Further, this result is expanded into a series with square-rootoperations and therefore is spread across the entire sound band.Therefore, it would be difficult to simply remove the noise from theamplitude-demodulated sound signal.

Thus, the noise component needs to be removed at a stage preceding theamplitude demodulation.

DFT executor 17 performs DFT on the baseband signal I(t), Q(t) at Lpoints on the frequency axis to obtain a discrete Fourier series X₀(n)of the baseband signal (step S4). Here, n denotes the index of thefrequency bins in the discrete Fourier series X₀(n). In this embodiment,the frequency bins are assigned indexes from −L/2 to (L/2−1), with theDC component being the 0-th bin.

For example, if L is 256, DFT at 256 points is performed to yield adiscrete Fourier series of complex numbers for the 256 points.Components X(−128) to X(127) corresponding to the respective frequencybins are thus obtained, with the DC component being the 0-th bin.

Amplitude spectrum calculator 18 then calculates an amplitude spectrum|X₀(n)| of the L points from the discrete Fourier series X₀(n) at the Lpoints (step S5). FIG. 4A shows the amplitude spectrum |X₀(n)| of thebaseband signal expressed by Equations 6 and 7.

Here, the frequency bin corresponding to the angular frequency ω_(C) ofthe carrier wave is the 0-th bin, which is the DC component of thediscrete Fourier series.

The frequency bins corresponding to the angular frequency ω_(S) of thesound content occur as a frequency bin N_(S) corresponding to the uppersideband and a frequency bin −N_(S) corresponding to the lower sideband,which are located symmetrically with respect to the 0-th bin. Afrequency bin N_(B) corresponding to the angular frequency ω_(B) of thenoise occurs only on the side of either one of the frequency binscorresponding to the upper sideband or the lower sideband.

Asymmetric component detector 19 then calculates the symmetry betweenthe upper sideband and the lower sideband in the amplitude spectrum|X₀(n)| of the L points. For calculating this symmetry, as shown in FIG.4B, the amplitude spectrum is inverted with respect to the centerfrequency bin, which is the 0-th bin (the DC component), to calculate aninverted amplitude spectrum |X′₀(n)| (step S6).

From the components corresponding to the upper sideband and the lowersideband in the amplitude spectrum of the L points, the symmetry D₀(n)at the L points is determined (step S7). Specifically, the symmetryD₀(n) is calculated by determining the ratio between the amplitude ofthe N-th frequency bin corresponding to the upper sideband and theamplitude of the −N-th frequency bin corresponding to the lower sidebandlocated symmetrically to the upper sideband.

If the amplitude of the N-th frequency bin and the amplitude of the−N-th frequency bin are equal, D₀(n) expressed in real number is 1. Ifthese amplitudes are different, D₀(n)≠1. If |X₀(n)|=0, it can beconsidered that D₀(n)=1.

When the amplitude of each frequency bin is expressed in dB withreference to the amplitude of the DC component, the difference betweenthe amplitude of the frequency bin corresponding to the upper sidebandand the amplitude of the frequency bin corresponding to the lowersideband is taken to calculate the symmetry D₀(n).

It may be determined that two components are symmetric (D₀(n)=1) if theabove-described amplitude ratio is within a predetermined range centeredat 1, or asymmetric (D₀(n)≠1) if the ratio is out of the predeterminedrange. The predetermined range is appropriately set according to factorssuch as the reception conditions of the AM broadcast wave or thespecifications and performance of reception device 10.

An asymmetric component is detected on the basis of the result of thesymmetry evaluation between the amplitude spectra |X₀(n)| and |X′₀(n)|shown in FIGS. 4A and 4B. That is, as shown in FIG. 4C, asymmetryappears between the N_(B)-th frequency bin (hereinafter referred to asan asymmetric frequency bin) corresponding to the angular frequencyω_(B) of the noise and the −N_(B)-th frequency bin located symmetricallywith respect to the DC component.

The −N_(B)-th frequency bin does not contain the actual noise component,and this must be noted when determining suppression factors (to bedescribed below).

For a signal containing a sound signal like an AM broadcast wave signal,a signal having a great amplitude relative to the actual sound signaloften becomes a problem as a noise. Therefore, for example, of thesymmetrically located two frequency bins detected as the asymmetriccomponents, the one having the greater amplitude may be selected as theactual asymmetric component (the component on which the noise issuperimposed). This enables the quality of the sound signal to be kepthigh.

Suppression factors W(n) for the L points are then set (step S8). Asshown in FIG. 5, W(N_(B))=0 is set for the asymmetric frequency binN_(B) detected by asymmetric component detector 19, and W(n)=1 is setfor the other frequency bins.

The suppression factor specified for the asymmetric frequency bin may beany number smaller than 1. W(N_(B)) for the asymmetric frequency binN_(B) detected by asymmetric component detector 19 may also be set insuch a manner that the asymmetric frequency bin N_(B) has the same valueas the amplitude spectrum |X₀(−N_(B))| of the asymmetric frequency bin−N_(B).

A certain number of adjacent frequency bins on both sides of theasymmetric frequency bin may also be assigned the same suppressionfactor. In any way, the frequency bins other than the asymmetricfrequency bin are assigned the suppression factor W(n) of a value largerthan the suppression factor W(N_(B)) for the asymmetric component to besuppressed. As mentioned above, the processing at step S7 may beperformed by suppression factor setter 20a.

Suppressor 20 then performs processing of multiplying each valuecorresponding to each frequency bin in the indiscrete Fourier seriesX₀(n) by the suppression factor W(n) set for the frequency bin, therebycalculating a new discrete Fourier series X₁(n) (step S9). FIG. 6 showsthe amplitude spectrum after this multiplication processing. It can beseen that the noise component in the baseband signal is suppressed.

For the discrete Fourier series X₁(n) calculated by suppressor 20, IDFTexecutor 21 performs inverse discrete Fourier transform at the L pointsto convert the series into a baseband signal in the time domain with thenoise component removed (step S10).

The baseband signal in the time domain with the noise component removedis expressed by Equations 9 and 10.

[Expression 9]

I(t)=½A′+½A′·m·cos(ω_(s) ·t)+½B′·cos(ω_(B) ·t)  (Equation 9)

[Expression 10]

Q(t)=0  (Equation 10)

Demodulator 22 amplitude-demodulates the signal expressed by Equations 9and 10 (step S11). The result is expressed by Equation 11.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 11} \right\rbrack & \; \\\begin{matrix}{{Y(t)} = \sqrt{{I(t)}^{2} + {Q(t)}^{2}}} \\{= \left\{ {\left( {{\frac{1}{2}A^{\prime}} + {\frac{1}{2}{A^{\prime} \cdot m \cdot {\cos \left( {\omega_{s} \cdot t} \right)}}}} \right)^{2} + (0)^{2}} \right\}^{\frac{1}{2}}} \\{= \left\{ {\frac{A^{\prime}}{2}\left( {1 + {m \cdot {\cos \left( {\omega_{S} \cdot t} \right)}}} \right)^{2}} \right\}^{\frac{1}{2}}} \\{= {\frac{A^{\prime}}{2}\left( {1 + {m \cdot {\cos \left( {\omega_{S} \cdot t} \right)}}} \right)}}\end{matrix} & \left( {{Equation}\mspace{14mu} 11} \right)\end{matrix}$

The signal expressed by Equation 11 is passed through a high-pass filter(HPF, not shown), which removes the carrier wave components from thesignal.

This yields a sound output that matches the single-tone signal containedin the AM broadcast wave (step S12).

As described above, according to this embodiment, a noise can be stablysuppressed with low computational complexity by utilizing the fact thatthe pair of sideband signals in the original signal is symmetricallydisposed on the frequency axis. This enables reception of a qualitysound signal.

Addressing Time Variation of Signal Reception Conditions

In receiving an actual AM broadcast wave signal, the above-describeddiscrete Fourier series X₀(n) is calculated at every predeterminedsampling time. Accordingly, the actual discrete Fourier series X₀(n) isrepresented as X₀(n,o), where n denotes the index of the frequency bins,as described above, and o denotes the index of the sampling times.

That is, a discrete Fourier series X₀(n,1) exists at the sampling timet1, and a discrete Fourier series X₀(n,2) exists at the sampling timet2.

Under a situation such that the actually received AM broadcast wavesignal and noise change little over time, it is not quite necessary toconsider time-varying terms in the discrete Fourier series. However, inpractice, due to causes such as the reception conditions, changes oftenoccur in these signals at every moment, especially in the number ofnoises and their amplitudes and frequencies.

Therefore, under such a time-varying situation, the suppression factorW(n) at step S8 needs to be determined as W(n,o) as with the discreteFourier series X₀(n,2). For example, if the amplitude of a noisecomponent having the angular frequency ω_(B) changes over time, thesuppression factor W(N_(B),o) for the corresponding frequency bin isvaried with time points according to the change in the amplitude|X₀(N_(B),o)| of the noise component, as shown in FIG. 7.

Thus, according to time variations of the signal and the receptionconditions, the suppression factor W(n,o) is calculated to suppress thenoise. This can prevent excessive suppression of the actual sound signalor insufficient noise suppression, and enables reception of a qualitysound signal.

While this embodiment has been described for an AM broadcast wave as anexample, this is not limitation. The technique disclosed in thisembodiment can be applied to any signal having the upper sideband andthe lower sideband whose amplitude spectra are symmetric with respect tothe center frequency.

This embodiment has illustrated the reception of an AM broadcast wavesignal containing one noise having a single frequency in thesound-content band. For a signal containing multiple noises, the noisescan also be suppressed in a similar manner by detecting the frequencybins corresponding to the noises as asymmetric components. For a signalcontaining noises in both the upper sideband and the lower sideband, thenoises can also be suppressed in a similar manner.

VARIATION 1

Variation 1 addresses the situation in which the angular frequency ofthe complex sine wave generated by NCO 14 has an offset from the angularfrequency of the carrier wave. In variation 1, the case will bedescribed in which the angular frequency of the complex sine wave ω′_(C)is such that ω′_(C)=ω_(C)+ω_(M).

The baseband in this case is expressed by Equation 12.

$\begin{matrix}\left\lbrack {{Expression}\mspace{14mu} 12} \right\rbrack & \; \\{{{V^{\prime}(t)} \cdot e^{{- j} \cdot {\omega^{\prime}}_{C} \cdot t}} = {{{V^{\prime}(t)} \cdot e^{{- j} \cdot {({\omega_{C} + \omega_{M}})} \cdot t}} = {{V^{\prime}(t)} \cdot \left\{ {{\cos \left( {\left( {\omega_{C} + \omega_{M}} \right) \cdot t} \right)} - {j \cdot {\sin \left( {\left( {\omega_{C} + \omega_{M}} \right) \cdot t} \right)}}} \right\}}}} & \left( {{Equation}\mspace{14mu} 12} \right)\end{matrix}$

Equation 12 indicates that the quadrature demodulation is performedwhile the angular frequency of the complex sine wave generated by NCO 14is offset by ω_(M) from the angular frequency ω_(C) of the carrier waveincluded in the AM broadcast wave signal.

FIG. 8A shows the result of expanding the baseband signal expressed byEquation 12, removing the carrier wave components of the angularfrequency ω_(C) by the LPF, and further performing DFT at the L pointsto obtain the discrete Fourier series of the baseband signal.

The carrier wave component having the angular frequency ω_(C)corresponds to the N_(M)-th frequency bin. This frequency bin is thecenter frequency bin that serves as the inversion axis in calculatingthe inverted spectrum. This frequency bin is offset by the amountcorresponding to the angular frequency ω_(M) from the DC component ofthe discrete Fourier series |X₀(n)|.

Similarly, the sound content having the angular frequency ω_(S) occursin the upper sideband and the lower sideband at the symmetric positionswith respect to the frequency bin N_(M), so that the sound contentbelongs to a frequency bin N_(M)+N_(S) and a frequency bin N_(M)−N_(S).The noise having the angular frequency ω_(B), which belongs to afrequency bin N_(M)+N_(B), occurs only in either one of the uppersideband and the lower sideband.

If the amount of offset of the angular frequency ω′_(C) of the complexsine wave from the angular frequency ω_(C) of the carrier wave is known,N_(M) is determined by calculation. Even if this amount of offset isunknown, the frequency bin having the greatest amplitude can be selectedamong frequency bins near the DC component of the amplitude spectrum|X₀(n)| and set as the center frequency bin.

In this case, as shown in FIGS. 8B and 8C, asymmetry appears between thepositions of the (N_(M)+N_(B))th and (N_(M)−N_(B))th frequency bins.

As described above, even if there is an offset between the angularfrequencies of the carrier wave in the AM broadcast wave signal and thecomplex sine wave generated by NCO 14, the center frequency bin for usein calculating the inverted spectrum can be set, irrespective of whetherthe amount of offset is known or unknown. The noise suppressionprocessing in the sound demodulation process can then be performedaccording to the flowchart shown in FIG. 3.

VARIATION 2

For calculating the discrete Fourier series X₀(n), the signal is dividedinto finite frequency intervals. Depending on the positions of thecarrier wave and the noise in their frequency bins, the symmetricpositions of frequency bins may deviate from proper positions. In thiscase, as shown in FIG. 9 for example, for the +k-th frequency bin, the−k-th frequency bin as well as several frequency bins on both sides ofthe −k-th frequency bin are extracted. The amplitude ratio is determinedbetween the +k-th frequency bin and the frequency bin having thegreatest amplitude (which is the (−k+1)th frequency bin in FIG. 9) amongthe extracted frequency bins, and the symmetry is evaluated. That is, anenvelope is calculated around the −k-th frequency bin, and the frequencybin corresponding to the maximum amplitude of the envelope is comparedwith the +k-th frequency bin in the symmetry evaluation.

Processing in the above manner can reduce the effect of deviation of thesymmetric positions of frequency bins due to the finitefrequency-division intervals. The number of points at which frequencybins are extracted for calculating the envelope is appropriatelydetermined according to factors such as the number of frequency bins inthe entire amplitude spectrum and the frequency bandwidth per dividedinterval.

In this embodiment and its variations, if multiple asymmetric componentsexist, the suppression factor W(n) can take an individual value for eachdetected asymmetric component. For example, if each asymmetric componenthas a different amplitude, a different suppression factor according tothe amplitude can be set for each asymmetric frequency bin. This enablesmore reliable suppression of the asymmetric components. Each of theasymmetric frequency bins may be assigned a different suppressionfactor, or some of the asymmetric frequency bins may be assigned adifferent suppression factor.

Individual suppression factors may also be set for frequency bins otherthan the asymmetric frequency bins. Each of the frequency bins otherthan the asymmetric frequency bins may be assigned a differentsuppression factor, or some of such frequency bins may be assigned adifferent suppression factor.

By setting an individual suppression factor for each frequency bin asabove, the effect of time variation of the received signal can beaccommodated. As mentioned above, when an actual AM broadcast wavesignal is received, the number of noises in the signal and theiramplitudes and frequencies often change at every moment.

For example, a frequency bin to which an asymmetric component belongsmay change over time. Then, if the suppression factor W(n) remains thesame after the change, the demodulated sound signal will appearunnatural. This also applies to the case in which a frequency bin towhich no asymmetric component belongs changes into an asymmetricfrequency bin over time.

Thus, the suppression factor W(n) itself can take an individual valuefor each frequency bin rather than a fixed value, and can be varied withthe time variation of the received signal. This enables demodulating andoutputting the sound signal of higher quality than the original signal.

There may be the case in which multiple asymmetric frequency bins existat a certain time point and only one of them changes into a frequencybin to which no asymmetric component belongs at the next time point. Inthis case, the suppression factor W(n) for only the changing frequencybin can be changed from 0 to 1. This enables demodulating and outputtingthe sound signal of higher quality than the original signal.

The amount of change of the suppression factor for each frequency binis, irrespective of whether the frequency bin is an asymmetric frequencybin, appropriately determined by taking into account such factors as thequality of the demodulated sound signal.

EMBODIMENT 2

Embodiment 2 is different from embodiment 1 mainly in that, in the noisesuppression processing, noise components are extracted on the basis ofcomparison with the carrier wave component, rather than by utilizing thesymmetry of the baseband signal on the frequency axis. Specifically, asshown in FIG. 10, embodiment 2 further includes: noise componentdetector 24 provided in parallel with asymmetric component detector 19between DFT executor 17 and first suppressor 20 b; second suppressor 25connected to noise component detector 24; and adjuster 26 provided at astage following first and second suppressors 20b and 25.

A sound demodulation process in this embodiment will be described withreference to a sound demodulation flowchart shown in FIG. 11. The sameprocessing as in the flow shown in FIG. 3 will not be described indetail.

Processing from step S1 to step S9 is the same as in the flow shown inFIG. 3 and will not be described in detail.

Processing from step S10 to step S12 is performed in parallel with theprocessing from step S6 to step S9.

In the amplitude spectrum |X₀(n)|, noise component detector 24determines the ratio between the amplitude of the frequency bin (the DCcomponent in this case) corresponding to the carrier wave and theamplitude of each frequency bin except the frequency bin of the DCcomponent. A frequency bin having an amplitude exceeding a predeterminedratio is detected as a noise component (step S10).

As shown in FIG. 12, if the modulation factor m is 1, the amplitude ofthe sound content in the AM broadcast wave signal is the amplitude ofthe carrier wave −6 dB. Even if m is equal to or greater than 1, theamplitude of the sound content would not exceed the amplitude of thecarrier wave −6 dB. Therefore, if the amplitude of the frequency binN_(B) is greater than the amplitude of the DC component −6 dB, thefrequency bin N_(B) is assumed to contain noise and is detected as anoise component.

Second suppressor 25 then sets a suppression factor W₂(n) for eachfrequency bin (step S11). The factor is set in a manner similar to thatillustrated in embodiment 1, and time variation of the receptionconditions may also be taken into account as in embodiment 1. Forexample, W₂(n)=0 is set for the frequency bin (hereinafter referred toas a noise frequency bin) corresponding to the noise component extractedat step S10. As in embodiment 1, the frequency bins other than the noisefrequency bin are assigned the suppression factor W(n) of a value largerthan the suppression factor W(N_(B)) for the noise component to besuppressed.

Second suppressor 25 multiplies the discrete Fourier factors X₀(n) atthe L points by the suppression factors W₂(n) for the L points tocalculate a new discrete Fourier series X₂(n) (step S12).

Adjuster 26 then contrasts the discrete Fourier series X₁(n) calculatedat step S9 with the discrete Fourier series X₂(n), and interpolates thediscrete Fourier series X₂(n) into the discrete Fourier series X₁(n) tocalculate a new discrete Fourier series X₃(n) (step S13).

At steps S14 to S16, a baseband signal in the time domain with the noisecomponent removed is generated from the discrete Fourier series X₃(n),and further the sound is demodulated. This processing is similar to theprocessing illustrated for steps S10 to S12 in FIG. 3 and therefore willnot be described.

As described above, according to this embodiment, a noise component isdetected on the basis of the ratio between the amplitude of thecomponent corresponding to the carrier wave and the amplitudes of theother frequency bins. This enables stable suppression of the noise withlow computational complexity, and therefore enables reception of aquality sound signal. In particular, with the configuration illustratedin embodiment 1, it is difficult to suppress noises of the sameamplitude superimposed respectively on two frequency bins locatedsymmetrically with respect to the component corresponding to the carrierwave.

With the configuration according to embodiment 2, such noises can bedetected on the basis of the ratios of their amplitudes to the amplitudeof the component corresponding to the carrier wave. This data can beinterpolated into the discrete Fourier series resulting from the noisesuppression based on the asymmetric components. This enables reliablenoise suppression.

If multiple noise components exist, the suppression factor W(n) can takean individual value for each detected noise component. For example, ifeach noise component has a different amplitude, a different suppressionfactor according to the amplitude can be set for each noise frequencybin. This enables more reliable suppression of the noise components.Each of the noise frequency bins may be assigned a different suppressionfactor, or some of the noise frequency bins may be assigned a differentsuppression factor.

Individual suppression factors may also be set for frequency bins otherthan the noise frequency bins. Each of the frequency bins other than thenoise frequency bins may be assigned a different suppression factor, orsome of such frequency bins may be assigned a different suppressionfactor.

As described for embodiment 1, by setting an individual suppressionfactor for each frequency bin, the effect of time variation of thereceived signal can be accommodated.

The suppression factor W(n) can take an individual value for eachfrequency bin rather than a fixed value, and can be varied with the timevariation of the received signal. This enables demodulating andoutputting the sound signal of higher quality than the original signal.

The amount of change of the suppression factor for each frequency binis, irrespective of whether the frequency bin is a noise frequency bin,appropriately determined by taking into account such factors as thequality of the demodulated sound signal.

In this embodiment, the result of detection based on the ratios betweenthe amplitude of the component corresponding to the carrier wave and theamplitudes of the other frequency bins is used as the interpolation datafor the result of detection based on the symmetry of the amplitudespectrum. The reason for this is that the configuration illustrated inembodiment 1 can provide more accurate noise detection and suppression.However, if highly accurate noise suppression is not required,asymmetric component detector 19, first suppressor 20 b, and adjuster 26may be eliminated from the configuration shown in FIG. 10. This canreduce the computational complexity, thereby increasing the processingspeed. This can also decrease the circuit scale required forcomputational processing for noise suppression.

In this case, the processing from step S10 to step S12 shown in FIG. 11replaces the processing from step S7 to S9 in the flowchart shown inFIG. 3.

If there is an offset between the angular frequency ω_(C) of the carrierwave and the angular frequency ω′_(C) of the complex sine wave generatedby NCO 14, the center frequency bin can be set in a manner similar tothat illustrated in variation 1. For example, if the angular frequencyω′_(C) of the complex sine wave has the same offset as in variation 1,noise component detector 24 compares the amplitude of the frequency binN_(M) and the amplitudes of the other frequency bins to detect noisecomponents.

Suppression factor setter 20 a shown in FIG. 2 may be added to theconfiguration shown in FIG. 10, or to the configuration shown in FIG. 10without asymmetric component detector 19, first suppressor 20 b, andadjuster 26.

INDUSTRIAL APPLICABILITY

The noise suppression devices in the present invention can suppressnoise in a received signal with low computational complexity andtherefore is especially useful when applied to reception devices for AMbroadcast wave signals.

REFERENCE MARKS IN THE DRAWINGS

10 reception device

11 antenna

12 amplifier

13 analog-to-digital converter (ADC)

14 numerically controlled oscillator (NCO)

15 mixer

16 quadrature demodulator

17 discrete Fourier transform (DFT) executor

18 amplitude spectrum calculator

19 asymmetric component detector

20 suppressor

21 inverse discrete Fourier transform (IDFT) executor

22 demodulator

24 noise component detector

25 second suppressor

26 adjuster

30 noise suppression device

1. A noise suppression device, comprising: a discrete Fourier transform executor that expands a baseband signal into a discrete Fourier series, the baseband signal being generated by quadrature-demodulating a received signal having an upper sideband signal and a lower sideband signal located symmetrically on a frequency axis with respect to a first angular frequency; an amplitude spectrum calculator that calculates an amplitude spectrum of frequency bins of the baseband signal expanded into the discrete Fourier series; an asymmetric component detector that detects, as an asymmetric frequency bin, a frequency bin corresponding to an asymmetric component in the amplitude spectrum by evaluating symmetry of the amplitude spectrum with respect to a center frequency bin corresponding to the first angular frequency; a suppressor that, in the discrete Fourier series expanded from the baseband signal, multiplies a value corresponding to the asymmetric frequency bin by a first factor, and multiplies a value corresponding to a frequency bin other than the asymmetric frequency bin by a second factor larger than the first factor; and an inverse discrete Fourier transform executor that performs inverse discrete Fourier transform on the discrete Fourier series processed by the suppressor and obtains a discrete-time signal.
 2. A noise suppression device, comprising: a discrete Fourier transform executor that expands a baseband signal into a discrete Fourier series, the baseband signal being generated by quadrature-demodulating a received signal having a carrier wave signal and a pair of sideband signals; an amplitude spectrum calculator that calculates an amplitude spectrum of frequency bins of the baseband signal expanded into the discrete Fourier series; a noise component detector that compares an amplitude of a center frequency bin corresponding to an angular frequency of the carrier wave signal and an amplitude of a frequency bin other than the center frequency bin, and detects a noise frequency bin having an amplitude whose ratio to the amplitude of the center frequency bin is higher than a predetermined value; a suppressor that, in the discrete Fourier series expanded from the baseband signal, multiplies a value corresponding to the noise frequency bin by a third factor, and multiplies a value corresponding to a frequency bin having an amplitude whose ratio to the amplitude of the center frequency bin is not higher than the predetermined value by a fourth factor larger than the third factor; and an inverse discrete Fourier transform executor that performs inverse discrete Fourier transform on the discrete Fourier series processed by the suppressor and obtains a discrete-time signal.
 3. The noise suppression device according to claim 1, further comprising: a noise component detector that compares an amplitude of a center frequency bin corresponding to an angular frequency of a carrier wave signal included in the received signal and an amplitude of a frequency bin other than the center frequency bin, and detects a noise frequency bin having an amplitude whose ratio to the amplitude of the center frequency bin is higher than a predetermined value; a second suppressor that, in the discrete Fourier series expanded from the baseband signal, multiplies a value corresponding to the noise frequency bin by a third factor, and multiplies a value corresponding to a frequency bin having an amplitude whose ratio to the amplitude of the center frequency bin is not higher than the predetermined value by a fourth factor larger than the third factor; and an adjuster that interpolates the discrete Fourier series processed by the second suppressor into the discrete Fourier series processed by the suppressor and calculates a new discrete Fourier series, wherein the discrete-time signal is obtained by the inverse discrete Fourier transform executor performing inverse discrete Fourier transform on the new discrete Fourier series.
 4. The noise suppression device according to claim 1, wherein the asymmetric frequency bin comprises a plurality of asymmetric frequency bins, and the first factor is capable of taking an individual value for each asymmetric frequency bin.
 5. The noise suppression device according to claim 1, wherein the frequency bin other than the asymmetric frequency bin comprises a plurality of frequency bins, and the second factor is capable of taking an individual value for each frequency bin other than the asymmetric frequency bin.
 6. The noise suppression device according to claim 2, wherein the noise frequency bin comprises a plurality of noise frequency bins, and the third factor is capable of taking an individual value for each noise frequency bin.
 7. The noise suppression device according to claim 2, wherein the frequency bin other than the noise frequency bin comprises a plurality of frequency bins, and the fourth factor is capable of taking an individual value for each frequency bin other than the noise frequency bin.
 8. The noise suppression device according to claim 1, wherein the asymmetric component detector detects the asymmetric frequency bin by evaluating the symmetry of the amplitude spectrum based on comparison between an amplitude of one frequency bin and the greatest amplitude among amplitudes of sequential frequency bins including a frequency bin located symmetrically to the one frequency bin with respect to the center frequency bin.
 9. The noise suppression device according to claim 1, wherein the center frequency bin is a frequency bin having the greatest amplitude near a DC component in the amplitude spectrum.
 10. A reception device, comprising: an antenna that receives an AM broadcast wave signal output from a broadcast station; an amplifier that amplifies the AM broadcast wave signal received from the antenna; an analog-to-digital converter that converts the amplified AM broadcast wave signal into a digital signal; a quadrature demodulator that quadrature-demodulates the digital signal to generate a baseband signal; a noise suppression device according to claim 1 that suppresses a noise included in the baseband signal to generate a discrete-time signal; and a demodulator that demodulates the discrete-time signal into a sound signal.
 11. A noise suppression method for suppressing a noise included in a received signal having an upper sideband signal and a lower sideband signal located symmetrically on a frequency axis with respect to a first angular frequency, the noise suppression method comprising: generating a baseband signal by mixing the received signal with a complex sine wave having a predetermined angular frequency; expanding the baseband signal into a discrete Fourier series; calculating an amplitude spectrum of frequency bins of the baseband signal expanded into the discrete Fourier series; detecting, as an asymmetric frequency bin, a frequency bin corresponding to an asymmetric component in the amplitude spectrum by evaluating symmetry of the amplitude spectrum with respect to a center frequency bin corresponding to the first angular frequency; in the discrete Fourier series expanded from the baseband signal, multiplying a value corresponding to the asymmetric frequency bin by a first factor, and multiplying a value corresponding to a frequency bin other than the asymmetric frequency bin by a second factor larger than the first factor; and performing inverse discrete Fourier transform on the discrete Fourier series in which the asymmetric component is suppressed and obtaining a discrete-time signal.
 12. A noise suppression method for suppressing a noise included in a received signal having a carrier wave signal and a pair of sideband signals, the noise suppression method comprising: generating a baseband signal by mixing the received signal with a complex sine wave having a predetermined angular frequency; expanding the baseband signal into a discrete Fourier series; calculating an amplitude spectrum of frequency bins of the baseband signal expanded into the discrete Fourier series; comparing an amplitude of a center frequency bin corresponding to an angular frequency of the carrier wave signal and an amplitude of a frequency bin other than the center frequency bin, and detecting a noise frequency bin having an amplitude whose ratio to the amplitude of the center frequency bin is higher than a predetermined value; in the discrete Fourier series expanded from the baseband signal, multiplying a value corresponding to the noise frequency bin by a third factor, and multiplying a value corresponding to a frequency bin having an amplitude whose ratio to the amplitude of the center frequency bin is not higher than the predetermined value by a fourth factor larger than the third factor; and performing inverse discrete Fourier transform on the discrete Fourier series in which a component corresponding to the noise frequency bin is suppressed and obtaining a discrete-time signal.
 13. The noise suppression method according to claim 11, further comprising: comparing an amplitude of a center frequency bin corresponding to an angular frequency of a carrier wave signal included in the received signal and an amplitude of a frequency bin other than the center frequency bin, and detecting a noise frequency bin having an amplitude whose ratio to the amplitude of the center frequency bin is higher than a predetermined value; in the discrete Fourier series expanded from the baseband signal, multiplying a value corresponding to the noise frequency bin by a third factor, and multiplying a value corresponding to a frequency bin having an amplitude whose ratio to the amplitude of the center frequency bin is not higher than the predetermined value by a fourth factor larger than the third factor; and interpolating the discrete Fourier series in which a component corresponding to the noise frequency bin is suppressed into the discrete Fourier series in which the asymmetric component is suppressed, and calculating a new discrete Fourier series, wherein the discrete-time signal is obtained by performing inverse discrete Fourier transform on the new discrete Fourier series.
 14. The noise suppression method according to claim 11, wherein the asymmetric frequency bin comprises a plurality of asymmetric frequency bins, and the first factor is capable of taking an individual value for each asymmetric frequency bin.
 15. The noise suppression method according to claim 11, wherein the frequency bin other than the asymmetric frequency bin comprises a plurality of frequency bins, and the second factor is capable of taking an individual value for each frequency bin other than the asymmetric frequency bin.
 16. The noise suppression method according to claim 12, wherein the noise frequency bin comprises a plurality of noise frequency bins, and the third factor is capable of taking an individual value for each noise frequency bin.
 17. The noise suppression method according to claim 12, wherein the frequency bin other than the noise frequency bin comprises a plurality of frequency bins, and the fourth factor is capable of taking an individual value for each frequency bin other than the noise frequency bin.
 18. The noise suppression method according to claim 11, wherein the detecting of the asymmetric frequency bin comprises detecting the asymmetric frequency bin by evaluating the symmetry of the amplitude spectrum based on comparison between an amplitude of one frequency bin and the greatest amplitude among amplitudes of sequential frequency bins including a frequency bin located symmetrically to the one frequency bin with respect to the center frequency bin.
 19. The noise suppression method according to claim 11, wherein the center frequency bin is a frequency bin having the greatest amplitude near a DC component in the amplitude spectrum.
 20. A reception method, comprising: receiving an AM broadcast wave signal output from a broadcast station; amplifying the AM broadcast wave signal; converting the amplified AM broadcast wave signal into a digital signal; generating a baseband signal by mixing the digital signal with a complex sine wave having a predetermined angular frequency; suppressing a noise included in the baseband signal to generate a discrete-time signal with the noise suppression method according to claim 11; and demodulating the discrete-time signal into a sound signal.
 21. The noise suppression device according to claim 3, wherein the noise frequency bin comprises a plurality of noise frequency bins, and the third factor is capable of taking an individual value for each noise frequency bin.
 22. The noise suppression device according to claim 3, wherein the frequency bin other than the noise frequency bin comprises a plurality of frequency bins, and the fourth factor is capable of taking an individual value for each frequency bin other than the noise frequency bin.
 23. The noise suppression device according to claim 2, wherein the center frequency bin is a frequency bin having the greatest amplitude near a DC component in the amplitude spectrum.
 24. A reception device, comprising: an antenna that receives an AM broadcast wave signal output from a broadcast station; an amplifier that amplifies the AM broadcast wave signal received from the antenna; an analog-to-digital converter that converts the amplified AM broadcast wave signal into a digital signal; a quadrature demodulator that quadrature-demodulates the digital signal to generate a baseband signal; a noise suppression device according to claim 2 that suppresses a noise included in the baseband signal to generate a discrete-time signal; and a demodulator that demodulates the discrete-time signal into a sound signal.
 25. The noise suppression method according to claim 13, wherein the noise frequency bin comprises a plurality of noise frequency bins, and the third factor is capable of taking an individual value for each noise frequency bin.
 26. The noise suppression method according to claim 13, wherein the frequency bin other than the noise frequency bin comprises a plurality of frequency bins, and the fourth factor is capable of taking an individual value for each frequency bin other than the noise frequency bin.
 27. The noise suppression method according to claim 12, wherein the center frequency bin is a frequency bin having the greatest amplitude near a DC component in the amplitude spectrum.
 28. A reception method, comprising: receiving an AM broadcast wave signal output from a broadcast station; amplifying the AM broadcast wave signal; converting the amplified AM broadcast wave signal into a digital signal; generating a baseband signal by mixing the digital signal with a complex sine wave having a predetermined angular frequency; suppressing a noise included in the baseband signal to generate a discrete-time signal with the noise suppression method according to claim 12; and demodulating the discrete-time signal into a sound signal. 